ModelEnsemble
- class pyapprox.interface.ModelEnsemble(functions, names=None)[source]
Bases:
objectWrapper class to allow easy one-dimensional indexing of models in an ensemble.
Methods Summary
__call__(samples)Evaluate a set of models at a set of samples.
evaluate_at_separated_samples(samples_list, ...)Evaluate a set of models at different sets of samples.
evaluate_models(samples_per_model)Evaluate a set of models at a set of samples.
Methods Documentation
- __call__(samples)[source]
Evaluate a set of models at a set of samples. The models must have the same parameters.
- Parameters:
- samplesnp.ndarray (nvars+1,nsamples)
Realizations of a multivariate random variable each with an additional scalar model id indicating which model to evaluate.
- Returns:
- valuesnp.ndarray (nsamples,nqoi)
The values of the models at samples
- evaluate_at_separated_samples(samples_list, active_model_ids)[source]
Evaluate a set of models at different sets of samples. The models need not have the same parameters.
- Parameters:
- samples_listlist[np.ndarray (nvars_ii, nsamples_ii)]
Realizations of the multivariate random variable model to evaluate each model.
- active_model_idsiterable
The models to evaluate
- Returns:
- values_listlist[np.ndarray (nsamples, nqoi)]
The values of the models at the different sets of samples
- evaluate_models(samples_per_model)[source]
Evaluate a set of models at a set of samples.
- Parameters:
- samples_per_modellist (nmodels)
The ith entry contains the set of samples np.narray(nvars, nsamples_ii) used to evaluate the ith model.
- Returns:
- values_per_modellist (nmodels)
The ith entry contains the set of values np.narray(nsamples_ii, nqoi) obtained from the ith model.